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A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants

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A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants

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dc.contributor.author Hernández, Luis es_ES
dc.contributor.author Baladrón Zorita, Carlos es_ES
dc.contributor.author Aguiar Pérez, Javier Manuel es_ES
dc.contributor.author Carro, Belén es_ES
dc.contributor.author Sanchez-Esguevillas, Antonio es_ES
dc.contributor.author Lloret, Jaime es_ES
dc.contributor.author Chinarro, David es_ES
dc.contributor.author Gómez Sanz, Jorge es_ES
dc.contributor.author Cook, Diane es_ES
dc.date.accessioned 2014-11-03T19:00:45Z
dc.date.available 2014-11-03T19:00:45Z
dc.date.issued 2013-01
dc.identifier.issn 0163-6804
dc.identifier.uri http://hdl.handle.net/10251/43823
dc.description.abstract [EN] Recent technological advances in the power generation and information technologies areas are helping to change the modern electricity supply system in order to comply with higher energy efficiency and sustainability standards. Smart grids are an emerging trend that introduce intelligence in the power grid to optimize resource usage. In order for this intelligence to be effective, it is necessary to retrieve enough information about the grid operation together with other context data such as environmental variables, and intelligently modify the behavior of the network elements accordingly. This article presents a multi-agent system model for virtual power plants, a new power plant concept in which generation no longer occurs in big installations, but is the result of the cooperation of smaller and more intelligent elements. The proposed model is not only focused on the management of the different elements, but includes a set of agents embedded with artificial neural networks for collaborative forecasting of disaggregated energy demand of domestic end users, the results of which are also shown in this article. es_ES
dc.description.sponsorship We would like to express our thanks to the coordinators of the project OptimaGrid for the information provided on MAS-based micro-grids, and the creators of a MAS INGENIAS methodology. This article has been partially funded by the project SociAAL (Social Ambient Assisted Living), supported by Spanish Ministry for Economy and Competitiveness, with grant TIN2011-28335-C02-01, by the Programa de Creacion y Consolidacion de Grupos de Investigacion UCM-Banco Santander for the group number 921354 (GRASIA group).
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) es_ES
dc.relation.ispartof IEEE Communications Magazine es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject CHALLENGES es_ES
dc.subject SECURITY es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.title A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/MCOM.2013.6400446
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2011-28335-C02-01/ES/SOCIAL AMBIENT ASSISTING LIVING - METHODS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UCM//921354/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres es_ES
dc.description.bibliographicCitation Hernández, L.; Baladrón Zorita, C.; Aguiar Pérez, JM.; Carro, B.; Sanchez-Esguevillas, A.; Lloret, J.; Chinarro, D.... (2013). A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants. IEEE Communications Magazine. 51(1):106-113. https://doi.org/10.1109/MCOM.2013.6400446 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1109/MCOM.2013.6400446 es_ES
dc.description.upvformatpinicio 106 es_ES
dc.description.upvformatpfin 113 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 51 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 265790
dc.contributor.funder Banco Santander
dc.contributor.funder Universidad Complutense de Madrid
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES


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